A NUMERICALLY STABLE REDUCED-GRADIENT TYPE ALGORITHM FOR SOLVING LARGE-SCALE LINEARLY CONSTRAINED MINIMIZATION PROBLEMS

被引：3
|
作者：
GOMES, HS [1 ]
MARTINEZ, JM [1 ]
机构：
[1] UNIV CAMPINAS, MECC, DEPT APPL MATHS, BR-13081 CAMPINAS, SP, BRAZIL
来源：
COMPUTERS & OPERATIONS RESEARCH | 1991年 / 18卷 / 01期
基金：
巴西圣保罗研究基金会;
关键词：
D O I：
10.1016/0305-0548(91)90038-S
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this paper we present a reduced-gradient type algorithm for solving large-scale linearly constrained minimization problems. During each iteration of the algorithm linear systems are solved using a preconditioned conjugate-gradient scheme. The preconditioning scheme uses orthogonal transformations, thus providing numerical stability. The total storage used by the algorithm may be predicted before beginning the calculations. We present some numerical experiments which confirm the reliability of the algorithm. © 1991.
引用
收藏
页码：17 / 31
页数：15
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